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Agronomy Journal 95:436-445 (2003)
© 2003 American Society of Agronomy

SOYBEAN

Double-Crop Soybean Leaf Area and Yield Responses to Mid-Atlantic Soils and Cropping Systems

Brian P. Jonesa, David L. Holshouser*,b, Marcus M. Alleyc, Jon K.F. Roygardc and Christine M. Anderson-Cookd

a Dep. of Crop and Soil Sci., The Penn State Univ., Univ. Park, PA 16802
b Virginia Polytechnic Inst. and State Univ., Tidewater Agric. Res. and Extension Center, 6321 Holland Road, Suffolk, VA 23437
c Dep. of Crop and Soil Environ. Sci., Virginia Polytechnic Inst. and State Univ., Blacksburg, VA 24061
d Dep. of Statistics, Virginia Polytechnic Inst. and State Univ., Blacksburg, VA 24061

* Corresponding author (dholshou{at}vt.edu)

Received for publication May 8, 2002.

   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Double-crop soybean (Glycine max L.) often yields less than full-season soybean, due in part to decreased leaf area development. Information is lacking on the effect of cropping system and plant-available water holding capacity (PAWHC) as affected by soil type on LAI in field-scale environments. The objectives of this research were to (i) determine the effect of three cropping systems and three soil types that vary in PAWHC on double-crop soybean leaf area and yield; and (ii) validate the LAI–yield relationship in a field-scale experiment. Soybean LAI and yield were measured at random geographically located positions during the 1999 to 2001 cropping seasons. During years of early season or little drought stress, LAI and yield were 1.1 to 1.2 units and 480 to 558 kg ha-1 less on the lowest PAWHC soil compared with the soil with the highest PAWHC. Soybean LAI and yield were reduced 0.4 units and 301 kg ha-1 when soybean experience early season drought stress and was not rotated. Under conditions of late-season drought stress, LAI and yield of rotated soybean were 1.6 units and 1350 kg ha-1 less on the lowest PAWHC soil. When soybean was not rotated and under conditions of late-season drought stress, LAI and yield were reduced by 2.9 units and 1770 kg ha-1 for the soil with the lowest PAWHC, and 1.6 units and 760 kg ha-1 for the soil with intermediate PAWHC. Soybean LAI was linearly related to yield only on the lowest PAWHC soil where LAI was low.

Abbreviations: DAP, days after planting • GPS, global positioning system • LAI, leaf area index • MG, maturity group • PAWHC, plant available water holding capacity


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
IN THE MID-ATLANTIC USA, soybean is commonly rotated with corn (Zea mays L.) and grown in a double-cropped system following the harvest of winter small grains, primarily wheat (Triticum aestivum L.) or barley (Hordeum vulgare L.). In this 3-crop in 2-yr system, corn and soybean are usually planted without tillage, but tillage is performed before small grain planting. A continuous no-tillage cropping system of corn, full-season soybean, small grain, and double-crop soybean (four crops in 3 yr) is used to a lesser extent. The advantage of the latter system is the greater ease of no-till seeding small grain into soybean stubble vs. corn stubble. Another system under investigation is a continuous no-tillage, continuous double-crop system (four crops in 2-yr) that includes barley, double-crop corn, wheat, and double-crop soybean (Alley and Roygard, 2002).

The double-crop soybean in the above systems is planted at postoptimal planting dates, often resulting in lower seed yield than in monocropped soybean systems (Egli, 1976; Wesley, 1999). Yield reduction of late planted, double-crop soybean has been attributed to a lack of sufficient vegetative growth (Ball et al., 2000b; Herbert and Litchfield, 1984) and increasing leaf area to maximize light interception is the primary reason that increased biomass is associated with higher yields in late-planted soybean (Wells, 1991; Board et al., 1992; Board and Harville, 1993). Early experiments by Shibles and Weber (1966) indicated that 95% light interception must be reached before the period of production of economic yield. Other experiments led these same authors to conclude that a leaf area index (LAI) of 3.2 is required for 95% interception (Shibles and Weber, 1965). Westgate (1999) stated that an LAI of 4.0 was needed to reach 95% light interception and it was essential that the canopy reach this critical LAI by flowering. Egli (1988) also observed that soybean lose yield potential if they fail to achieve 95% light interception by beginning flower or R1 development stage as defined by Fehr and Caviness (1977).

Entomologists have stated that insect defoliation thresholds that are based on LAI rather than percent defoliation are more meaningful (Herbert et al., 1992; Higley, 1992). In defoliation experiments, Malone et al. (2002) showed significant linear decreases in yield when LAI values fell below 3.5 to 4.0, but no yield loss if LAI was maintained above this level. Soybean insect pest management would therefore benefit from knowing LAI present in a field and how cultural practices and within- or between-field soil changes affect leaf area development.

Cropping systems that differ in rotation or soybean cultivar maturity may affect LAI development. Several studies concluded that soybean yielded more when grown in rotation (Bhowmik and Doll, 1982; Crookston et al., 1991; Meese et al., 1991), but the effect on LAI has not been explored. Later-maturing cultivars are more likely to meet minimum leaf area requirements than early maturing cultivars (Jones, 2002; Holshouser and Whittaker, 2002). Continuous double-crop systems require that an early maturing soybean cultivar be grown to ensure timely small grain planting (Alley and Roygard, 2002). This combination of late planting with an early maturing cultivar could result in even lower LAI than traditional double-crop systems.

Lack of moisture can also impact leaf area development. Ball et al. (2000a) observed recommended populations for optimum planting dates were insufficient for late-planted soybean because of the failure of these populations to achieve maximum light interception, especially in years of low rainfall. Similarly, in an early soybean production system, higher populations were required to maximize yield only where drought stress limited leaf area production (Holshouser and Whittaker, 2002). In that study, soils with higher plant-available water holding capacity (PAWHC), and therefore less susceptibility to drought, were able to achieve critical leaf area requirements at an earlier stage and at lower populations. Therefore, it would be expected that leaf area development would proceed at different rates on soils of differing PAWHC. In the mid-Atlantic region, early season intermittent drought is common (Holshouser and Whittaker, 2002); therefore, moisture stress is likely to also affect early season vegetative growth and leaf area development, especially on low PAWHC soils.

Cropping system and PAWHC as determined by soil type might all affect the attainment of critical LAI by flowering and thus influence the maximum potential soybean yield. Because soils can vary greatly within a field in the Mid-Atlantic region, site-specific management tactics to increase leaf area may possibly be a means to increase field-average yields. In addition, knowledge of LAI variability in the field could aid insect pest management. But, the effect of cropping system and soil type on LAI and yield needs documenting in field-scale environments. Furthermore, the LAI–yield relationship (Shibles and Weber, 1965; Westgate, 1999; Malone et al., 2002) has not been validated in large fields. The objectives of this study were to (i) determine the effect of three cropping systems that vary in cultivar maturity, tillage, and rotation, and the effect of three soil types that vary in PAWHC on double-crop soybean leaf area index and yield; and (ii), validate the LAI–yield relationship in a field-scale experiment.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Field experiments were conducted in 1999, 2000, and 2001 on a 24-ha field at Camden Farm in Port Royal, VA (38°09'N, 77°08'W). The site was part of the larger mid-Atlantic Regional Interdisciplinary Cropping Systems Project (Alley and Roygard, 2002), a long-term study evaluating three mid-Atlantic cropping systems under rain-fed conditions. On initiation of the study in 1997, Natural Resource Conservation Service scientists conducted an Order I soil survey of the site. Soil types as mapped were a Bojac 1, Bojac 2, Wickham 3, and Wickham 4. The Bojac 1 and Bojac 2 soils are a sandy loam and loamy sand, respectively (coarse loamy, mixed, thermic Typic Hapludults), and are relatively low in PAWHC (10.6 and 7.3 cm m-1 PAWHC, respectively). The Wickham soils are both sandy loams (fine loamy, mixed, thermic Ultic Hapludalfs), and are considered more productive soils (11.8 cm m-1 PAWHC). Due to the similarities between the Wickham soil types, they were combined for analysis purposes.

Cropping system 1 is a standard system used throughout much of the mid-Atlantic region and consists of three crops in 2 yr: no-till corn, conventional-till winter wheat, and no-till double-crop soybean. Cropping system 2 is a continuous no-tillage rotation of four crops in 3 yr used to a lesser extent in the mid-Atlantic region: no-till corn, no-till full-season soybean, no-till wheat, and no-till double-crop soybean. Cropping system 3 is experimental and includes a continuous no-tillage, four crops in a 2-yr rotation: no-till wheat, no-till double-crop soybean, no-till barley, and no-till double-crop corn.

Experimental design of this continuing study was a randomized complete block with three replications. Within each block, seven 610-m long and 18-m wide plots allowed the inclusion of all rotational phases of the three cropping systems (Fig. 1) . Specifically, there were two plots for cropping system 1, three plots for cropping system 2, and two plots for cropping system 3. Table 1 lists the crops and year planted for each rotational phase of the three cropping systems since the beginning of the experiment.



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  		Fig. 1. Aerial photograph of the cropping systems experiment taken in 2001 showing scale and soil type divisions.

 

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  		Table 1. Crops and year planted for each cropping system and plot for the mid-Atlantic Regional Interdisciplinary Cropping Systems Project, 1997–2001.

 
Data were collected from treatment rotations that included double-crop soybean during the 1999–2001 growing seasons (Table 1). Cropping system 1 (three crops in 2 yr) and cropping system 2 (four crops in 3 yr) were no-till planted with Pioneer brand (Pioneer, a Dont Co., Johnston, IA) ‘9492’ soybean (MG IV) on 30 June in 1999, 25 June in 2000, and 29 June in 2001 following wheat harvest. Cropping system 3 (four crops in 2 yr) was no-till planted with Asgrow (Monsanto, St. Louis, MO) brand ‘AG3701’ soybean (MG III) following wheat harvest on the same dates. An earlier maturing cultivar was needed in this rotation to enable timely barley planting immediately after soybean harvest. All soybean were seeded with a 23-row John Deere brand JD 1780 Max-Emerge II (Deere and Co.y, Moline, IL) planter using 38-cm row spacing.

Within each cropping system, 21 to 30 randomly selected locations were established to measure plant population, LAI, and yield. The locations were arranged so that 7 to 10 measurements were taken from each treatment strip. Variability of soil types across the treatment strips resulted in an unequal number of measurement locations being assigned to each soil type. As a result, 13, 28, and 30 measurement locations were included in the Bojac 1, Bojac 2, and Wickham soils, respectively, in 1999. In 2000, Bojac 1 had a total of 15 locations, Bojac 2 had 27, and Wickham had 23. In 2001, Bojac 1 had a total of 9 measurements, Bojac 2 had 39, and Wickham had 42. The relatively low number of measurements for the Bojac 1 was because of the smaller area that this soil type covers in the experiment, vs. the larger areas of the Bojac 2 and Wickham soil types (Fig. 1).

Latitude and longitude were determined for all sample locations using a differentially corrected global positioning system (GPS) receiver with 1-m accuracy (Trimble AG 132, Trimble Navigation, Sunnyvale, CA). Plant population, LAI, and yield were measured at the same geo-referenced locations within the field, allowing relationships between these variables to be established.

Plant population was measured 20 to 26 d after planting (DAP) by placing an 85-cm diameter circular frame randomly three times within 2 m of the pre-established and geo-referenced measurement location and counting the number of plants that fell within the frame.

Leaf area index was measured at the same geo-referenced locations with a LAI-2000 plant canopy analyzer following sampling methods described by LI-COR (1992, p. D1-3) and Welles and Norman (1991). The LAI-2000 uses the relationship between fractions of direct and indirect radiation intercepted by the canopy and canopy structure, or gap fraction analysis, to estimate LAI (Welles and Norman, 1991). Both the sensor and the plants in the plot must be shaded for accurate determination of LAI. Therefore, all readings were taken on cloudy days or in the early morning or late afternoon with a constructed shade preventing direct sunlight from reaching the sensor or plants. Leaf area index was measured 64 DAP in 1999, 53 and 73 DAP in 2000, and 41, 54, and 69 DAP in 2001.

Rainfall data were obtained from a weather station located adjacent to the experiment. Potential evapotranspiration rates were calculated using the FAO reference Penman-Monteith equation (Eq. [1]) (Allen et al., 1998). The FAO Penman-Monteith equation estimates the evapotranspiration from a reference grass surface and provides a standard to which evapotranspiration from other crops can be related (Alley and Roygard, 2002). The ETo was calculated as:

[1]
where ETo is reference evapotranspiration (mm d-1), Rn is net radiation at the crop surface (MJ m-2 d-1), G is soil heat flux density (MJ m-2 d-1), T is air temperature at 2-m height (°C), u2 is windspeed at 2-m height (m s-1), es is saturation vapor pressure (kPa), ea is actual vapor pressure (kPa), es - ea is saturation vapor pressure deficit (kPa), {Delta} is slope vapor pressure curve (kPa °C), and {gamma} is the psychrometric constant (kPa °C-1). The data for ETo calculation was obtained from the weather station located adjacent to the experiment.

Soil profile water content was measured with TDR probes (Moisturepoint, Environmental Sensors, Victoria, BC, Canada) in 2000 and 2001. Time domain reflectometry probes were arranged such that, for each study year, there were at least two probes for each soil type within each crop rotation. Due to the rotation, sites were in different locations in the 3 yr of the study. Probes were inserted vertically to a depth of 1.2 m. Volumetric soil water content measurements were recorded weekly using a Moisturepoint soil moisture measurement instrument (Model MP-917, Environmental Sensors, Victoria, BC, Canada). Measurements were made downward along the probe in 15-cm increments for the first 30 cm, after which measurements were made along the probe in 30-cm increments until a depth of 120 cm.

Soybean cultivars AG3701 (four crops in 2 yr) and 9492 (three crops in 2 yr and four crops in 3 yr) were harvested 12 Oct. 1999 and 3 Nov. 1999, respectively, and 12 Oct. 2000 and 13 Nov. 2000, respectively. In 2001, an early freeze occurred on 9 October, terminating soybean growth. As a result, all soybean plots were harvested on 20 October. Harvest was accomplished with a John Deere 9610 combine equipped with a yield monitor (Greenstar) and GPS with satellite differential correction. All yield data were geo-referenced by the combine at time of harvest. This allowed yield data to be compared with geo-referenced plant population density and LAI data.

Previous geostatistical analysis of the spatial variability in this field (Anderson-Cook et al., 1999) demonstrated that spatial correlation did not extend beyond 18 to 27 m once soil differences had been taken into account. Leaf area index and yield measurements in this experiment were approximately 60 m apart within a plot and analysis of these data confirmed lack of spatial correlation. Therefore, the MIXED procedure of SAS (SAS Inst., 1997) was utilized to examine significance of cropping system and soil type effects and their interactions. The LSMEANS statement was used to compute the least-squares means of the fixed effects. The PDIFF option of the LSMEANS statement, which utilizes Fisher's Protected LSD, was used to request that the differences in LS-means be displayed for comparison. Leaf area index measurements were taken over time from the same experimental units; therefore, the REPEATED statement within the MIXED procedure was used to test hypotheses about the LAI factors and their interactions. Mean separations were considered significant if p values were <=0.05. The REG procedure of SAS (SAS Inst., 1997) was utilized to determine relationships between LAI and yield.


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
CONCLUSIONS
 REFERENCES
 
In 1999, rainfall lagged far behind ETo and early season vegetative growth was less than in the succeeding years (Fig. 2) . In general, dry conditions prevailed until reproductive development was initiated in early August (Fig. 2A). Afterward, timely and adequate rainfall met the crop's ETo needs. Figure 3A shows percent volumetric soil water content for the three soil types and further represents times of drought stress. Rainfall remained consistent with or exceeded ETo rates early in 2000 (Fig. 2B). Nearly half of the total rainfall was received within 1 mo of planting. Rainfall was below average in August 2000 and ETo was greater than cumulative rainfall. Rainfall events occurred until late September (R6 soybean stage), but no additional rainfall occurred before harvest on 12 October or 13 November for AG3701 and 9492, respectively. Figure 3B shows percent volumetric soil water content over time for the three soils in the top 120 cm of soil. Although soil water content decreased slightly during the early reproductive stages, rainfall replenished the soil profile during the later reproductive stages. This indicated that soybean was using the soil moisture reserves, as well as the rainfall, during the pod and seed filling stages. Cumulative rainfall shown on Fig. 2C does not fully characterize the 2001 year. Of the total rainfall, 308 mm, or 88%, was received during the first 52 DAP, until 19 August. From 19 August until harvest on 20 October (114 DAP) only 43 mm of rainfall occurred. Cumulative rainfall exceeded ETo until the late pod to early seed development stages, but lack of rainfall in late September and October resulted in a deficit of cumulative rainfall compared with ETo. Volumetric soil water content better shows this decline in soil water (Fig. 3C). Therefore, three distinct environments occurred during the course of this experiment. In 1999, rainfall was less than ETo needs during vegetative development stages, but adequate during reproductive stages. The environment was nearly opposite in 2001, with rainfall exceeding ETo during vegetative development stages, but becoming increasingly dry through the reproductive stages. Although ETo exceeded rainfall at 90 DAP in 2000, timely rain fell throughout the season and little water stress occurred.



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  		Fig. 2. Daily rainfall (solid bars), cumulative rainfall (solid line), and cumulative evapotranspiration rates (dotted line) over time in 1999, 2000, and 2001. Arrows indicate LAI measurement dates and development stages for each cultivar.

 


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  		Fig. 3. Volumetric soil water content of the top 120 cm of three soil types, averaged over cropping system. Arrows indicate LAI measurement dates and development stages for each cultivar.

 
Soil type and cropping system affected LAI and yield in 1999, but no interaction between the two factors was present (Table 2). The Wickham and Bojac 1 soil had greater LAI at 64 DAP and yield than the Bojac 2 soil, indicating that early season drought affected soybean to a greater extent on the lowest PAWHC soil. Cropping system also affected LAI, but to a lesser extent than soil type. The three crops in 2 yr system had higher LAI than the four crops in 3 yr system for all soil types; LAI of the four crops in 2 yr cropping treatment was intermediate. Yield followed a similar trend, but the four crops in 2 yr system also experienced lower yield than the three crops in 2 yr system. Although genetic differences in cultivar might explain the lower yield of the four crops in 2 yr rotation, the lower yield is most likely due the timing of drought stress during 1999. After the onset of flowering approximately 40 to 45 DAP, AG3701 was a full development stage ahead of 9492. Ritchie et al. (1997) stated that the ability of a soybean crop to compensate for stresses decreases as it ages from R1 to R5.5. AG3701, being in a later stage of development was therefore less able to compensate from the reproductive-stage drought stress experienced during that year. But, the reason for the differences in yield between the three crops in 2 yr and four crops in 3 yr systems cannot be attributed to rainfall timing because the same cultivar (9492) was used in both systems. The four crops in 3 yr system included a full-season soybean crop grown in the previous year (Table 1), whereas the other two systems had not included soybean in the rotation in the 2 previous years. Several studies have concluded that soybean yields less when grown continuously vs. in an annual rotation (Bhowmik and Doll, 1982; Crookston et al., 1991; Meese et al., 1991). In an experiment conducted at three locations in Minnesota and Wisconsin that spanned 8 to 11 yr and including 28 environments, similar results were found (Porter et al., 1997). Their analysis determined that soybean in an annual rotation with corn yielded 10% more than continuous soybean, but yield of first-year soybean following 5 yr of corn increased 18%. Furthermore, yields declined steadily with increasing years of nonrotated soybean. The results presented here tend to support this and other rotation research.


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  		Table 2. Soybean leaf area index measured 64 d after planting and yield for three cropping systems and three soil types, 1999. Cultivars 9492 and AG3701 were in the R4 and R5 development stages, respectively, at time of LAI measurement.

 
Soil type, but not cropping system, affected LAI and yield in 2000 (Table 3). Leaf area index increased over time and responded similarly to differences in soil type for both LAI measurement dates. The Wickham soil, with the highest PAWHC, had greater LAI and yield for all cropping systems than the Bojac 2 soil type with the lowest PAWHC. Leaf area index and yield for the Bojac 1 was intermediate to the Wickham and Bojac 2.


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  		Table 3. Soybean leaf area index measured at 53 and 73 d after planting and yield for soil type averaged over cropping system treatments, 2000. Cultivars 9492 and AG3701 were in the R2 and R3, and R4 and R5 development stages for the 53 and 73 d-after-planting LAI measurements, respectively.

 
Cropping system and soil type affected both LAI and yield in 2001 (Table 4). As in 2000, LAI increased over time for all cropping systems regardless of soil type or cropping system. The Wickham soil type had greater LAI for all measurement dates and seed yield than the Bojac 2 soil in all cropping systems. There was essentially no rainfall during seed filling (Fig. 2C) and the crop was depleting soil moisture reserves (Fig. 3C); therefore, it is likely that the greater PAWHC of the Wickham soil greatly contributed to final seed yield. Soybean planted on the drier Bojac 2 soil type used the available soil water early, and thus very little was available when conditions became droughty.


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  		Table 4. Soybean leaf area index measured at 41, 54, and 69 d after planting and yield for three cropping systems and three soil types, 2001. Cultivars 9492 and AG3701 were in the V7 and R1, R2 and R3, and R4 and R5 development stages for the 53 and 73 d after planting LAI measurements, respectively.

 
Within soil types, LAI response to cropping system and soybean cultivar varied according to time of LAI measurement in 2001 (Table 4). Initially on the Wickham soil type, there was no difference in LAI between crop rotations. By the second and third measurement dates, however, LAI was greater in cropping system 1 (three crops in 2 yr) and cropping system 2 (four crops in 3 yr) than in cropping system 3 (four crops in 2 yr). This may be explained by maturity differences between cultivars use in these systems. At 54 DAP, AG3701 was in the late pod development stage (R4) and leaf area development was slowing. In contrast, 9492 was in the beginning pod development stage (R3), where the rate of leaf area development had not yet slowed. For the Bojac 1 soil type, a difference in LAI between cropping systems was not observed until the third measurement date. At this time, soybean in both cropping systems 2 and 3 were observed to have a lower LAI than in rotation 1. The response for the Bojac 2 soil was quite different. For all LAI measurements, LAI was lowest for cropping system 2 (four crops in 3 yr). No difference between cropping systems 1 and 3 were observed until the last measurement date, which can be explained by differences in maturity as described above.

Yield of cultivar 9492 was affected by an early killing frost that occurred on 9 October. The earlier maturing cultivar AG3701 had already reached full maturity by this time, but the later maturing 9492 was in the late seed-filling stage. The frost caused premature leaf death of the MG IV cultivar and likely had a negative impact on seed yield, especially in those areas of the field with lower LAI. With this in mind, it is likely that yields of 9492 would have been greater and differences in yield between cropping systems would have been similar to LAI differences if the frost had not occurred. Since the same cultivar was used for cropping systems 1 and 2, one would not suspect that frost would have differentially affected yield between the systems. However, the greater LAI on the Bojac 1 soil of cropping system 1 likely helped to maintain yield in that system. Frost probably affected the two rotations equally on the Wickham soil since LAI did not differ.

Once again in 2001, a rotation effect was observed. However, in this year, the four crops in 3 yr rotation had required two previous soybean plantings instead of one during the course of this experiment (Table 1). This is compared to cropping systems 1 and 3 (three crops in 2 yr and four crops in 2 yr) where soybean was grown 2 yr apart. Since initiation of the study, there has been only one previous soybean planting in these cropping systems. Therefore, the rotation effect may have been enhanced over 1999.

Another contrast to 1999 regarding this rotation effect was the interaction with soil type. On the Wickham soil, there was no difference in LAI or yield between cropping systems 1 and 2. But, the rotation effect became increasingly evident as the soil's PAWHC decreased. Although cropping system 2 (four crops in 3 yr) yields were less than cropping system 1 (three crops in 2 yr) for both Bojac soils, significant decreases in LAI appeared earlier for the lower PAWHC Bojac 2 (Table 4). The more intensive soybean rotation also reduced yields 25 and 31% for the Bojac 1 and Bojac 2, respectively, compared with the three crops in 2 yr system. These data confirm past research that indicated a greater advantage of rotation in lower-yielding environments (Porter et al., 1997).

In 1999, cropping system had no effect on the LAI–yield relationship, but soil type altered the response (Fig. 4) . A significant linear relationship between LAI and yield was evident only for the Bojac 2 soil, where LAI varied from 2.0 to 4.5. On this soil, yield increased 508 kg ha-1 for every unit increase in LAI. No relationship between LAI and yield was observed with the other soils, but LAI values ranged from 3.8 to 5.0 at the R4 and R5 stage for 9492 and AG3701, respectively. Although LAI measurements were not taken at the flowering stages (R1 and R2), LAI at that stage were likely approaching 3.5 to 4.0, a level where past research indicated that the LAI–yield relationship is less obvious (Malone et al., 2002).



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  		Fig. 4. Relationship of soybean yield to leaf area index at 64 d after planting on three soil types, 1999. Cultivars 9492 and AG3701 were in the R4 and R5 development stages, respectively.

 
In 2000, no significant relationship was evident for any soil or crop rotation at either measurement date (Fig. 5) . It should be noted that LAI was usually above 3.5 to 4.0. Previous research has proposed that leaf area no longer becomes a limiting factor in soybean yield at these LAI levels or above (Shibles and Weber, 1965; Westgate, 1999; Malone et al., 2002). The variation in yield at a specific LAI indicated that factors unrelated to LAI were affecting yield in this large field. This experiment covered a total land area of 24 ha and the distance between data collection locations within a plot were approximately 60 m. It is not unexpected to see large yield variation over such a large area when all sources of yield variation are unknown.



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  		Fig. 5. Relationship of soybean yield to leaf area index at (A) 53 and (B) 73 days after planting on three soil types, 2000. Cultivars 9492 and AG3701 were in the R2 and R3, and R4 and R5 development stages, respectively.

 
In 2001, cropping system had no effect on the LAI–yield relationship for any measurement date, but soil type affected the relationship (Fig. 6) . Yield increased 1089 and 389 kg ha-1 per unit of LAI increase at 41 and 54 DAP, respectively, on the Bojac 2 soil type, but no relationship between yield and LAI existed for the Wickham or Bojac 1 soils. As the crop matured, differences between soils still existed and a relationship between LAI and yield was also observed on the Bojac 1 soil (Fig. 6C). For both Bojac soils, yield increased with increasing LAI at the same rate of 442 kg ha-1 per unit increase in LAI. No relationship between LAI and yield was observed at any date for the Wickham soil, and LAI was greater than 3.5 in most instances by 54 DAP at the R2 and R3 stages for 9492 and AG3701, respectively (Fig. 6B). Several locations within the Bojac 1 soil had LAI of <3.5 to 4.0 by the R2 and R3 stages, but no relationship was evident except for the 69 DAP measurement (Fig. 6C). Still, this may reflect some relationship between LAI and yield when LAI levels are low. More measurements (only nine were taken in 2001) may have improved model fit. In contrast, data from the Bojac 2 soil, with the lowest PAWHC, confirmed past research (Shibles and Weber, 1965; Westgate, 1999; Malone et al., 2002) and indicated a LAI–yield relationship in leaf area–restricted soybean systems.



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  		Fig. 6. Relationship of soybean yield to leaf area index at (A) 41, (B) 54, and (C) 69 days after planting on three soil types, 2001. Cultivars 9492 and AG3701 were in the V7 and R1, R2 and R3, and R4 and R5 development stages, respectively.

 

   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
REFERENCES
 
Planting soybean late, following a small grain crop reduces the time available to accumulate sufficient LAI for yield maximization; therefore, the double-crop soybean system qualifies as a LAI-limited environment. However, as indicated by these data, LAI may not be limited in all cropping systems or on all soils. Therefore, the degree of LAI-increasing practices, such as increasing plant population and decreasing row spacing, should be implemented on a site-specific basis to ensure the highest yield potential and lowest input cost. Soil type was by far the most influential factor on double-crop soybean LAI and yield in this experiment. The lower PAWHC Bojac 2 soil restricted LAI to a level that affected yield in 2 of 3 yr. In addition to soil type, the cropping system that included the earlier maturing AG3701 cultivar developed less leaf area that the later maturing 9492 cultivar in 1 of 3 yr. Therefore, cultivar choice should also be considered when deciding on what level of LAI-increasing practice should be implemented.

These data confirmed the advantage of rotating soybean with another crop on at least an annual basis. When double-crop soybean followed a full-season soybean crop, LAI and yield was reduced in 2 of 3 yr. More importantly, this rotation effect tended to be a greater detriment during years of less rainfall and on soils with lower PAWHC. In 2001, a year with substantial moisture stress late in the season, only the lower PAWHC soils were affected by the lack of rotation. Furthermore, in a relatively low moisture stress year (2000), the lack of rotation did not affect LAI or yield. Therefore, knowing and understanding soil capacity to provide adequate moisture to the crop should affect the choice of cropping system and the management of these systems.

These data also validated previously documented LAI–yield relationships. Although much yield and LAI variability existed in this large-scale experiment, yield increased with LAI on the lowest PAWHC soil and during years of drought stress. This usually occurred only when LAI was <3.5 to 4.0.

These data document how field variability and cropping system can affect soybean leaf area and yield. But, more detailed experiments under more controlled environments may be needed to further quantify the effect of environmental parameters, especially soil moisture, on leaf area production. More study on determining the impact of plant-available water, as determined by evapotranspiration rates and precipitation, on this relationship will be necessary. Site-specific management practices that attempt to maximize and maintain leaf area for double-cropping soybean systems in the mid-Atlantic states must consider variations in plant-available water. Finally, even if a better understanding of LAI and yield variability is acquired, more adequate methods of measuring LAI in large-field settings, such as a form of remote sensing, is in order before large-scale determination of leaf area, and accurate determination of LAI–yield relationships, can become a reality.


   ACKNOWLEDGMENTS
 
The authors acknowledge the Foundation for Agronomic Research, the United Soybean Board, the Virginia Soybean Board, and the Virginia Agricultural Council for their financial support and to Mr. John Davis, Mr. Tommy Hicks, and Mr. Reuben Lakin of Camden Farm for their cooperation in providing their time, land, equipment, and labor for this research.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 





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